Human interface devices include touch control systems that are based on touch sensing surfaces, e.g., pads, screens, etc., using capacitive sensors that change capacitance values when touched. Transforming the touch(es) on the touch sensor into one or more touch locations is non-trivial. Tracking one or more touches on the touch sensor is also challenging. Advanced touch control systems are capable of detecting not only a single touch and/or movement on a touch sensing surface such as a touch screen, but also so-called multi-touch scenarios in which a user touches more than one location and/or moves more than one finger over the respective touch sensing surface. e.g., gesturing.
Key challenges of multi-touch systems are: limited processing speed of low cost systems, such as processing capabilities of, for example but not limited to, 8-bit microcontroller architectures as these architectures may be unable to do advanced math for processing the respective signals generated by the touch sensing device. There may also exist limited touch scanning performance, for example the entire system may be unable to reasonably sample the entire plane of the touch sensor or screen every “frame.” Other challenges include having enough program memory space to provide for touch location determination programs that are concise, modular and general purpose. Limited random access memory (RAM) space may make the touch determination system unable to store multiple entire “images” of the touch detection and location(s) thereof simultaneously.
Hence, there exists a need to improve and simplify touch determination methods. Conventional solutions were threshold based and required complex computations. Hence, there is a need for touch determination methods that are more robust and less computation intensive. Furthermore, there exists a need for high quality multi-touch decoding, in particular, a method and/or system that can be implemented with, for example but not limited to, a low-cost 8-bit microcontroller architecture.